$1 billion to build AI models with emotional intelligence

Have you ever wondered what it would be like if AI could truly understand and respond to your emotions? In today's episode of The Deep Dive, we're exploring a groundbreaking AI funding story that shifts the focus from sheer computational power to emotional intelligence. We're delving into the mission of a new startup, Humans in Darrett, which aims to create AI that is not just smart, but emotionally intelligent. This episode challenges the conventional notion of AI as cold and machine-like, and instead, envisions a future where AI can empathize and collaborate effectively with humans.

Leading this innovative venture is Eric Zelickman, a former Stanford PhD student and a key figure in the AI community. Zelickman has a background in logic and reasoning, having contributed significantly to advancements in AI language models. His work introduced the concept of a "scratch pad" for internal reasoning, which helped improve AI's logical flow. Now, he's making a bold leap into the realm of emotions, raising a staggering $1 billion at a $4 billion valuation to bring his vision to life. Investors are not just betting on the idea of emotionally intelligent AI; they are backing Zelickman's expertise and track record in the field.

This episode unpacks Zelickman’s critique of current AI models, which he argues are too detached and fail to maintain emotional continuity in conversations. Humans in Darrett aims to address this by developing AI that remembers emotional contexts and can empathize with users. The implications of such technology are profound, extending beyond improved chatbots to potentially revolutionizing fields like cancer research, education, and diplomacy. By fostering better human collaboration through empathy, AI could become a powerful ally in tackling complex global challenges. The episode leaves us pondering whether the $4 billion valuation is justified and what the future holds if AI can genuinely understand human emotions and motivations.

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Have you ever wondered what it would take for AI to truly remember you?

In this episode of "The Deep Dive," we explore a groundbreaking development in artificial intelligence: solving the long-term memory problem. Imagine interacting with an AI that doesn't just forget your previous conversations but remembers and builds on them, much like a human would. This is the vision behind a new startup called Super Memory, which has recently secured $2.6 million in seed funding from industry giants like Google AI chief Jeff Dean and Cloudflare CTO Dane Necht. The involvement of such prominent figures indicates the significance of tackling memory persistence in AI, a challenge that has long been a stumbling block for large language models.

Meet Dravya Shah, the 19-year-old prodigy behind Super Memory.

Originally from Mumbai, Dravya Shah's journey into the tech world began with a simple bot that formatted tweets into screenshots, which he sold to a company called Hypefury. This entrepreneurial spirit led him to the United States for university, and eventually to a pivotal role at Cloudflare. It was there that Shah's idea for Super Memory took shape, with encouragement from advisors like Dane Necht. His innovative approach to AI memory caught the attention of tech leaders, prompting them to support his vision of creating a universal memory API that could revolutionize how AI interacts with data.

Revolutionizing AI with a universal memory API.

Super Memory's technology is designed to manage and utilize vast amounts of unstructured data—ranging from files and documents to chat logs and multimedia content—by extracting key insights and building a comprehensive knowledge graph. This approach not only enhances the AI's ability to recall information but also improves performance by structuring data into a relational map, allowing for more efficient and context-aware retrieval. As a result, applications can achieve deeper personalization and understanding. With backing from investors and early customers like a fintech company and an AI video editor, Super Memory is poised to lead a transformation in AI, turning forgetful tools into personalized partners that genuinely remember and understand user interactions over time. This shift could redefine the future of AI, making it an integral part of our daily lives.

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What does it take to power the future of AI?

How much compute power is truly necessary to unlock AI's full potential? This episode delves into a groundbreaking partnership that could redefine the AI landscape. We're exploring the colossal deal between AMD and OpenAI, involving billions of dollars and, intriguingly, gigawatts of power. As we peel back the layers of this agreement, we uncover the staggering scale of AMD's commitment to supply 6 gigawatts of power—enough to energize millions of homes. This episode challenges listeners to ponder the immense infrastructure required to fuel the ambitions of AI giants.

Meet the key players behind the scenes

Our guest today is an industry insider with deep insights into the tech world, particularly in the realm of artificial intelligence and computing power. They bring a wealth of knowledge about AMD's latest technological advancements and OpenAI's strategic maneuvers in securing resources from multiple tech giants. With a background in both hardware and software development, our guest provides a nuanced perspective on how these partnerships are shaping the future of AI and the potential risks and rewards involved.

A high-stakes gamble in the AI arms race

The episode provides a high-level overview of the AMD-OpenAI partnership, focusing on the technical and financial intricacies. AMD is betting big with its next-gen Instinct Mi450 chips, scheduled for deployment in 2026, and OpenAI is poised to become a major shareholder, contingent on AMD meeting ambitious performance targets. This deal is part of OpenAI's broader strategy, which includes commitments from Nvidia and Broadcom, and a massive Stargate initiative for data center expansion. The discussion highlights the intense competition and collaboration required to meet the astronomical compute demands of AI's future, as OpenAI diversifies its suppliers to avoid dependency.

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